Boosting Classifiers with Tightened L0-Relaxation Penalties.
Noam GoldbergJonathan EcksteinPublished in: ICML (2010)
Keyphrases
- ensemble learning
- weak classifiers
- randomized trees
- weak learners
- ensemble classifier
- boosting algorithms
- feature selection
- improving classification accuracy
- boosting framework
- decision stumps
- multiclass classification
- majority voting
- multiple classifier systems
- adaboost algorithm
- machine learning algorithms
- boosted classifiers
- base classifiers
- multi class
- linear classifiers
- training data
- meta learning
- learning algorithm
- decision trees
- strong classifier
- accurate classifiers
- iterative algorithms
- class labels
- support vector
- training set
- classifier combination
- ensemble methods
- discriminative classifiers
- classifier ensemble
- naive bayes
- classification trees
- loss function
- multiple classifiers
- bayesian classifiers
- weighted voting
- classification algorithm
- individual classifiers
- binary classification problems
- feature subset
- binary classifiers
- classification systems
- classification models
- cost sensitive